Lagrangian dual interior-point methods for semidefinite programs
Mituhiro Fukuda (mituhirois.titech.ac.jp)
Abstract: This paper proposes a new predictor-corrector interior-point method for a class of semidefinite programs, which numerically traces the central trajectory in a space of Lagrange multipliers. The distinguished features of the method are full use of the BFGS quasi-Newton method in the corrector procedure and an application of the conjugate gradient method with an effective preconditioning matrix induced from the BFGS quasi-Newton method in the predictor procedure. Some preliminary numerical results are reported.
Keywords: Semidefinite Program, Linear Program Over Convex Cones, Second-Order Cone Program, Primal-Dual Interior-Point Method, Predictor-Corrector Method, Lagrangian Dual, Central Trajectory, BFGS Quasi-Newton Method, Conjugate Gradient Method.
Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )
Category 2: Convex and Nonsmooth Optimization (Convex Optimization )
Category 3: Linear, Cone and Semidefinite Programming (Second-Order Cone Programming )
Citation: SIAM Journal on Optimization Vol 12, No.4, 1007-1031 (2002).
Entry Submitted: 04/03/2001
Modify/Update this entry
|Visitors||Authors||More about us||Links|
Search, Browse the Repository
Give us feedback
|Optimization Journals, Sites, Societies|